The Data Analytics Research Project is undertaken by the student as the capstone component of the MSc Data Analytics. Preparation for the project commences from the outset of the programme, where students' research mindset and skills are nurtured and developed. Data Analytics Research Project Preparation 2 is delivered in a three week block at the end of semester 2. By this time, students will have been working with their supervisor on scoping and defining their research problem, and carrying out their data analysis. This module focuses on preparing students for effectively presenting and communicating their analysis and their findings in the form of a multimedia artefact, a client report and a research paper, exploring in particular the affordances of different modes of communication and different means of visualisation to ensure and enhance impact. The module revisits and build upon the earlier treatment topics such as ethical, legal, social, organisational and sustainability matters within which findings can be framed, in the context of multimedia artefact, the client report, and the research paper.
Multimedia Artefacts
- Multimedia communication tools (e.g., video, infographics, interactive dashboards).
- Creating and integrating multimedia elements such as videos, infographics, and interactive visuals.
- Developing a multimedia presentation that effectively communicates research insights.
Client Report Writing
- Structure and content of client reports, including executive summaries, methodology sections, findings, and recommendations.
- Crafting clear, actionable reports tailored to a non-academic audience.
- Writing and critiquing client reports, focusing on clarity and practical implications.
Research Paper Development
- Structure and components of a research paper (introduction, literature review, methodology, results, discussion, conclusion).
- Writing and formatting academic papers, including adherence to academic standards and citation styles.
- Drafting and peer-reviewing research papers.
Data Visualisation Techniques
- Advanced visualization techniques and tools (e.g., interactive charts, heat maps, network diagrams).
- Choosing appropriate visualizations for different types of data and research findings.
- Creating and refining visualizations to enhance communication of key insights.
Ethical and Legal Considerations
- Revisiting ethical issues related to data privacy, consent, and data handling.
- Ensuring research compliance with legal and ethical standards.
- Case studies and scenarios related to ethical and legal challenges in data research.
Data Bias
- Sampling, Measurement, Observer and Survivorship
- Statistical techniques for identifying bias in datasets
- How to reduce bias during model training and evaluation (re-sampling, de-biasing word embeddings, and fairness-aware algorithms).
Social, Organisational, and Sustainability Impacts
- Framing research findings within broader social, organizational, and the Sustainable Development Goals.
- Analysing and articulating the impact of research on various stakeholders and contexts.
- Incorporating ethical and sustainability considerations into final research presentations and reports.
This module will be completed with 24 hours of workshop and lectures complemented with 76 hours of independent learning.
For full-time students, the workshops and lectures will be completed over a three week period taking place at the end of semester 2.
For part-time students, the workshops and lectures will take place throughout the semester on a weekly basis.
The workshops and lectures will involve individual and group discussions and activities as well as presentations, case study analyses and online activities. Some class time may take place in the laboratory to demonstrate software that can be used for multimedia presentations, but it is expected that the majority of the work on the digital artefact will take place in the self-directed learning hours.
| Module Content & Assessment | |
|---|---|
| Assessment Breakdown | % |
| Other Assessment(s) | 100 |